def test_positivity_calculator(self, data):
ipt = IPTW(data, treatment='A', stabilized=True)
ipt.regression_models(model_denominator='L', print_results=False)
ipt.fit()
ipt.positivity()
npt.assert_allclose(ipt._pos_avg, 1)
npt.assert_allclose(ipt._pos_sd, 0.456435, rtol=1e-5)
npt.assert_allclose(ipt._pos_min, 2 / 3)
npt.assert_allclose(ipt._pos_max, 2)
def test_positivity_calculator(self, data):
ipt = IPTW(data, treatment='A', outcome='Y')
ipt.treatment_model(model_denominator='L', print_results=False)
ipt.marginal_structural_model('A')
ipt.fit()
ipt.positivity()
npt.assert_allclose(ipt._pos_avg, 1)
npt.assert_allclose(ipt._pos_sd, 0.456435, rtol=1e-5)
npt.assert_allclose(ipt._pos_min, 2 / 3)
npt.assert_allclose(ipt._pos_max, 2)
def test_unstabilized_positivity_warning(self, data):
ipt = IPTW(data, treatment='A', stabilized=False)
ipt.regression_models(model_denominator='L', print_results=False)
ipt.fit()
with pytest.warns(UserWarning):
ipt.positivity()